Muhammad Imran

Muhammad Imran
Qatar Computing Research Institute · Hamad Bin Khalida University

PhD

About

120
Publications
42,951
Reads
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4,263
Citations
Introduction
My interdisciplinary research focuses on natural language processing, social computing, and applied machine learning. I analyze social media communications during time-critical situations using big data analysis techniques such as data mining, machine learning, and deep neural networks. I develop novel computational models, techniques, and technologies useful for stakeholders to gain situational awareness and actionable information during emergencies.
Additional affiliations
December 2014 - present
Qatar Computing Research Institute
Position
  • Researcher
April 2013 - December 2014
Qatar Computing Research Institute
Position
  • PostDoc Position
June 2012 - September 2012
Qatar Computing Research Institute
Position
  • Research Associate
Education
September 2009 - April 2013
Università degli Studi di Trento
Field of study
  • Computing Science
January 2005 - March 2007
Mohammad Ali Jinnah University
Field of study
  • Computer Science
January 2004 - January 2005
Oracle Corporation
Field of study

Publications

Publications (120)
Article
Full-text available
Recent research in disaster informatics demonstrates a practical and important use case of artificial intelligence to save human lives and suffering during natural disasters based on social media contents (text and images). While notable progress has been made using texts, research on exploiting the images remains relatively under-explored. To adva...
Article
Natural disasters, such as floods, tornadoes, or wildfires, are increasingly pervasive as the Earth undergoes global warming. It is difficult to predict when and where an incident will occur, so timely emergency response is critical to saving the lives of those endangered by destructive events. Fortunately, technology can play a role in these situa...
Article
Full-text available
Formal response organizations perform rapid damage assessments after natural and human-induced disasters to measure the extent of damage to infrastructures such as roads, bridges, and buildings. This time-critical task, when performed using traditional approaches such as experts surveying the disaster areas, poses serious challenges and delays resp...
Article
Geolocation information is important for humanitarian organizations to gain situational awareness and deliver timely aid during disasters. Towards addressing the problem of recognizing locations, i.e., Location Mention Recognition (LMR), within social media posts during such disasters, past studies mainly focused on proposing techniques that assume...
Article
Full-text available
The development of a system that monitors social media continuously for general landslide-related content using a landslide classification model to identify and retain the most relevant information is described and validated. The system harvests photographs in real-time from these data and tags each image as landslide or not-landslide. A training m...
Article
Full-text available
The COVID‐19 pandemic initially caused worldwide concerns about food insecurity. Tweets analyzed in real‐time may help food assistance providers target food supplies to where they are most urgently needed. In this exploratory study, we use natural language processing to extract sentiments and emotions expressed in food security‐related tweets early...
Preprint
This paper presents an online system that leverages social media data in real time to identify landslide-related information automatically using state-of-the-art artificial intelligence techniques. The designed system can (i) reduce the information overload by eliminating duplicate and irrelevant content, (ii) identify landslide images, (iii) infer...
Article
Full-text available
Flood events cause substantial damage to infrastructure and disrupt livelihoods. Timely monitoring of flood extent helps authorities identify severe impacts and plan relief operations. Remote sensing through satellite imagery is an effective method to identify flooded areas. However, critical contextual information about the severity of structural...
Preprint
Natural disasters, such as floods, tornadoes, or wildfires, are increasingly pervasive as the Earth undergoes global warming. It is difficult to predict when and where an incident will occur, so timely emergency response is critical to saving the lives of those endangered by destructive events. Fortunately, technology can play a role in these situa...
Article
Full-text available
As the world struggles with several compounded challenges caused by the COVID-19 pandemic in the health, economic, and social domains, timely access to disaggregated national and sub-national data are important to understand the emergent situation but it is difficult to obtain. The widespread usage of social networking sites, especially during mass...
Article
The development of a system that monitors social media continuously for general landslide-related content using a landslide classification model to identify and retain the most relevant information is described and validated. The system harvests photographs in real-time from these data and tags each image as landslide or not-landslide. A training m...
Preprint
Full-text available
Detecting fights from still images shared on social media is an important task required to limit the distribution of violent scenes in order to prevent their negative effects. For this reason, in this study, we address the problem of fight detection from still images collected from the web and social media. We explore how well one can detect fights...
Preprint
Full-text available
The widespread usage of social networks during mass convergence events, such as health emergencies and disease outbreaks, provides instant access to citizen-generated data that carry rich information about public opinions, sentiments, urgent needs, and situational reports. Such information can help authorities understand the emergent situation and...
Preprint
Lack of global data inventories obstructs scientific modeling of and response to landslide hazards which are oftentimes deadly and costly. To remedy this limitation, new approaches suggest solutions based on citizen science that requires active participation. However, as a non-traditional data source, social media has been increasingly used in many...
Preprint
Full-text available
Recent research in disaster informatics demonstrates a practical and important use case of artificial intelligence to save human lives and sufferings during post-natural disasters based on social media contents (text and images). While notable progress has been made using texts, research on exploiting the images remains relatively under-explored. T...
Preprint
Full-text available
Humanitarian actions require accurate information to efficiently delegate support operations. Such information can be maps of building footprints, building functions, and population densities. While the access to this information is comparably easy in industrialized countries thanks to reliable census data and national geo-data infrastructures, thi...
Article
Full-text available
Social media platforms have become fundamental tools for sharing information during natural disasters or catastrophic events. This paper presents SEDOM-DD (Sub-Events Detection on sOcial Media During Disasters), a new method that analyzes user posts to discover sub-events that occurred after a disaster (e.g., collapsed buildings, broken gas pipes,...
Preprint
Full-text available
Images shared on social media help crisis managers in terms of gaining situational awareness and assessing incurred damages, among other response tasks. As the volume and velocity of such content are really high, therefore, real-time image classification became an urgent need in order to take a faster response. Recent advances in computer vision an...
Preprint
Full-text available
Social networks are widely used for information consumption and dissemination, especially during time-critical events such as natural disasters. Despite its significantly large volume, social media content is often too noisy for direct use in any application. Therefore, it is important to filter, categorize, and concisely summarize the available co...
Article
Catastrophic events create uncertain situations for humanitarian organizations locating and providing aid to affected people. Many people turn to social media during disasters for requesting help and/or providing relief to others. However, the majority of social media posts seeking help could not properly be detected and remained concealed because...
Article
Full-text available
The world is facing enormous challenges, ranging from climate change to extreme poverty. The 2030 Agenda for Sustainable Development and its 17 Sustainable Development Goals (SDGs) were adopted by United Nations Member States in 2015 as an operational framework to address these challenges. The SDGs include No Poverty, Quality Education, Gender Equa...
Conference Paper
During an ongoing disaster event, real-time image classification becomes important for crisis managers for situ-ational awareness and crisis response tasks. Current advances in image classification methods enable the crisis informatics community to develop models for real-time image classification and facilitate humanitarian response tasks. Providi...
Preprint
Full-text available
During a disaster event, images shared on social media helps crisis managers gain situational awareness and assess incurred damages, among other response tasks. Recent advances in computer vision and deep neural networks have enabled the development of models for real-time image classification for a number of tasks, including detecting crisis incid...
Chapter
Responding to natural disasters, such as earthquakes, floods, and wildfires, is a laborious task performed by on-the-ground emergency responders and analysts. Social media has emerged as a low-latency data source to quickly understand disaster situations. While most studies on social media are limited to text, images offer more information for unde...
Book
Responding to natural disasters, such as earthquakes, floods, and wildfires, is a laborious task performed by on-the-ground emergency responders and analysts. Social media has emerged as a low-latency data source to quickly understand disaster situations. While most studies on social media are limited to text, images offer more information for unde...
Chapter
The ever-increasing popularity of social media platforms has transformed the way in which information is shared during disasters and mass emergencies. Information that emanates from social media, especially in the early hours of a disaster when little-to-no information is available from other traditional sources, can be extremely valuable for emerg...
Article
People increasingly use Social Media (SM) platforms such as Twitter and Facebook during disasters and emergencies to post situational updates including reports of injured or dead people, infrastructure damage, requests of urgent needs, and the like. Information on SM comes in many forms, such as textual messages, images, and videos. Several studies...
Preprint
Responding to natural disasters, such as earthquakes, floods, and wildfires, is a laborious task performed by on-the-ground emergency responders and analysts. Social media has emerged as a low-latency data source to quickly understand disaster situations. While most studies on social media are limited to text, images offer more information for unde...
Data
The past several years have witnessed a huge surge in the use of social media platforms during mass convergence events such as health emergencies, natural or human-induced disasters. These non-traditional data sources are becoming vital for disease forecasts and surveillance when preparing for epidemic and pandemic outbreaks. In this paper, we pres...
Article
The past several years have witnessed a huge surge in the use of social media platforms during mass convergence events such as health emergencies, natural or human-induced disasters. These non-traditional data sources are becoming vital for disease forecasts and surveillance when preparing for epidemic and pandemic outbreaks. In this paper, we pres...
Article
Full-text available
This resource was created to support researchers who might be newly conducting crisis informatics research in light of the pandemic of 2020. It also might support creation of new course syllabi on related topics. It has been produced by members of the crisis informatics research community in May 2020 to consolidate and organize the literature on in...
Preprint
Full-text available
The past several years have witnessed a huge surge in the use of social media platforms during mass convergence events such as health emergencies, natural or human-induced disasters. These non-traditional data sources are becoming vital for disease forecasts and surveillance when preparing for epidemic and pandemic outbreaks. In this paper, we pres...
Article
This article describes a method for early detection of disaster-related damage to cultural heritage. It is based on data from social media, a timely and large-scale data source that is nevertheless quite noisy. First, we collect images posted on social media that may refer to a cultural heritage site. Then, we automatically categorize these images...
Conference Paper
Full-text available
Multimedia content in social media platforms provides significant information during disaster events. The types of information shared include reports of injured or deceased people, infrastructure damage, and missing or found people, among others. Although many studies have shown the usefulness of both text and image content for disaster response pu...
Preprint
Full-text available
Rapid damage assessment is one of the core tasks that response organizations perform at the onset of a disaster to understand the scale of damage to infrastructures such as roads, bridges, and buildings. This work analyzes the usefulness of social media imagery content to perform rapid damage assessment during a real-world disaster. An automatic im...
Preprint
Time-critical analysis of social media streams is important for humanitarian organizations to plan rapid response during disasters. The crisis informatics research community has developed several techniques and systems to process and classify big crisis data on social media. However, due to a variety of different datasets used in the literature, it...
Preprint
Full-text available
Multimedia content in social media platforms provides significant information during disaster events. The types of information shared include reports of injured or deceased people, infrastructure damage, and missing or found people, among others. Although many studies have shown the usefulness of both text and image content for disaster response pu...
Chapter
The use of social media platforms such as Twitter by affected people during crises is considered a vital source of information for crisis response. However, rapid crisis response requires real-time analysis of online information. When a disaster happens, among other data processing techniques, supervised machine learning can help classify online in...
Article
Social Media (SM) contain a wealth of information that could improve the situational awareness of Emergency Managers during a crisis, but many barriers stand in the way. These include information overload, making it impossible to deal with the flood of raw posts, and lack of trust in unverified crowdsourced data. The purpose of this project is to b...
Article
Full-text available
Social media platforms such as Twitter provide convenient ways to share and consume important information during disasters and emergencies. Information from bystanders and eyewitnesses can be useful for law enforcement agencies and humanitarian organizations to get firsthand and credible information about an ongoing situation to gain situational aw...
Article
Microblogging platforms such as Twitter are widely used by eyewitnesses and affected people to post situational updates during mass convergence events such as natural and man-made disasters. These crisis-related messages disperse among multiple classes/categories such as infrastructure damage, shelter needs, information about missing, injured, and...
Article
Full-text available
Traditional post-disaster assessment of damage heavily relies on expensive geographic information system (GIS) data, especially remote sensing image data. In recent years, social media have become a rich source of disaster information that may be useful in assessing damage at a lower cost. Such information includes text (e.g., tweets) or images pos...
Article
Huge amounts of data generated on social media during emergency situations is regarded as a trove of critical information. The use of supervised machine learning techniques in the early stages of a crisis is challenged by the lack of labeled data for that event. Furthermore, supervised models trained on labeled data from a prior crisis may not prod...
Article
The growing importance of social media in conflicts and crises is accompanied by an ever-increasing research interest in the crisis informatics field in order to identify potential benefits and develop measures against the technology’s abuse. This special issue sets out to give an overview of current research on the use of social media in conflicts...
Conference Paper
Full-text available
Over the last few years, extensive research has been conducted to develop technologies to support humanitarian aid tasks. However, many technologies are still limited as they require both manual and automatic approaches, and more importantly, are not ready to be integrated into the disaster response workflows. To tackle this limitation, we develop...
Article
Full-text available
People increasingly use microblogging platforms such as Twitter during natural disasters and emergencies. Research studies have revealed the usefulness of the data available on Twitter for several disaster response tasks. However, making sense of social media data is a challenging task due to several reasons such as limitations of available tools t...
Article
Full-text available
People are increasingly sharing information on social media during disaster events. This information could be valuable to emergency responders, but there remain challenges for using it to inform response efforts---including filtering relevant information from the large volumes of noise. Previous research has largely focused on identifying informati...
Article
Full-text available
During a new disease outbreak, frustration and uncertainties among affected and vulnerable population increase. Affected communities look for known symptoms, prevention measures, and treatment strategies. On the other hand, health organizations try to get situational updates to assess the severity of the outbreak, known affected cases, and other de...
Preprint
Full-text available
Extensive research on social media usage during emergencies has shown its value to provide life-saving information, if a mechanism is in place to filter and prioritize messages. Existing ranking systems can provide a baseline for selecting which updates or alerts to push to emergency responders. However, prior research has not investigated in depth...
Article
Full-text available
Online Social Media, such as Twitter, Facebook and WhatsApp, are important sources of real-time information related to emergency events, including both natural calamities, man-made disasters, epidemics, and so on. There has been lot of recent work on designing information systems that would be useful for aiding post-disaster relief operations, as w...
Conference Paper
In recent times, humanitarian organizations increasingly rely on social media to search for information useful for disaster response. These organizations have varying information needs ranging from general situational awareness (i.e., to understand a bigger picture) to focused information needs e.g., about infrastructure damage, urgent needs of aff...
Preprint
Traditional post-disaster assessment of damage heavily relies on expensive GIS data, especially remote sensing image data. In recent years, social media has become a rich source of disaster information that may be useful in assessing damage at a lower cost. Such information includes text (e.g., tweets) or images posted by eyewitnesses of a disaster...
Conference Paper
Full-text available
Social media platforms such as Twitter provide convenient ways to share and consume important information during disasters and emergencies. Information from bystanders and eyewitnesses can be useful for law enforcement agencies and humanitarian organizations to get firsthand and credible information about an ongoing situation to gain situational aw...
Preprint
Full-text available
People increasingly use microblogging platforms such as Twitter during natural disasters and emergencies. Research studies have revealed the usefulness of the data available on Twitter for several disaster response tasks. However, making sense of social media data is a challenging task due to several reasons such as limitations of available tools t...